Course in Actuarial Evaluation of Autonomous Vehicle Accidents
Online course of 300 h in actuarial evaluation of autonomous vehicle accidents. 6 modules covering Directive 2009/138/EC (Solvency II), IFRS 17 (insurance contracts) and R. Assigned tutor and open enrolment.
Take the controls.
Run a real engineering trade-off from this field. Move the sliders, watch the model react in real time and beat the challenge.
What you will be able to do
Frame the actuarial problem of the vehicle at different levels of automation.
Define exposure measures based on usage data and driving mode.
Estimate frequency and severity using appropriate statistical models.
Design products, prices and reinsurance structures for the new claims profile.
Calculate and monitor reserves under Solvency II and IFRS 17.
Establish model governance in an environment of scarce data.
Develop an integrating project in actuarial evaluation.
Who it's for
- Motor pricing actuary who wants to specialise in actuarial evaluation of autonomous vehicle accidents.
- Autonomous vehicle risk analyst who wants to specialise in actuarial evaluation of autonomous vehicle accidents.
- Reserving actuary who wants to specialise in actuarial evaluation of autonomous vehicle accidents.
- Insurance data scientist who wants to specialise in actuarial evaluation of autonomous vehicle accidents.
- Motor reinsurance manager who wants to specialise in actuarial evaluation of autonomous vehicle accidents.
- Mobility actuarial consultant who wants to specialise in actuarial evaluation of autonomous vehicle accidents.
- Engineering or science graduates seeking to enter motor insurance.
What you'll work with
- Directive 2009/138/EC (Solvency II)
- IFRS 17 (insurance contracts)
- Royal Legislative Decree 8/2004 (compulsory motor vehicle insurance)
- Law 35/2015 (traffic accident compensation scale)
- UNECE Regulation No. 157 (automated lane-keeping systems)
- Implementing Regulation (EU) 2022/1426 (type-approval of automated driving systems)
- Directive 2009/103/EC (motor vehicle insurance)
6 modules · 300 h
1.1Scarcity of claims experience1.2Change in the structure of frequency1.3Change in severity and repair cost1.4Shift of liability1.5Heterogeneity of technologies1.6Operational design domain and its effect on exposure1.7Sector vocabulary and acronyms1.8Available data sources1.9Portfolio maturation horizon1.10Exercise: identifying the critical assumptions
2.1Kilometres driven by driving mode2.2Manufacturer data and access to it2.3Disengagement and intervention data2.4Incident and near-miss data2.5Public studies and their comparability2.6Definition of the exposure unit2.7Segmentation by operational design domain2.8Data quality and biases2.9Simulation data as a complement2.10Practice: defining the exposure of a portfolio
3.1Frequency models with scarce data3.2Bayesian methods and prior information3.3Credibility and blending of sources3.4Severity and repair cost models3.5Separation of liability between parties3.6Technology evolution scenarios3.7Sensitivity analysis3.8Confidence intervals and their communication3.9Validation with emerging experience3.10Practice: estimating the technical premium
4.1Product design for the automated vehicle4.2Premium split between policyholder and manufacturer4.3Software and cybersecurity coverages4.4Deductibles and limits4.5Agreements with manufacturers4.6Reinsurance of the new exposure4.7Accumulation risk from systemic defects4.8Frequent tariff review4.9Communication with the customer4.10Practice: designing a product and its price
5.1Reserves with limited experience5.2Long-tail claims and product liability5.3Monitoring real experience5.4Early warning indicators5.5Review of assumptions and documentation5.6Governance of the actuarial model5.7Reporting to the supervisor5.8Independent validation5.9Lessons from emerging experience5.10Practice: portfolio monitoring dashboard
6.1Choice of segment and technology6.2Definition of exposure6.3Frequency and severity model6.4Estimation of the technical premium6.5Product and reinsurance design6.6Reserving and monitoring plan6.7Sensitivity analysis6.8Governance and documentation6.9Actuarial report6.10Project defence
How you'll learn
100 % online training on the SEIUM campus, with downloadable material, recorded classes and an assigned technical tutor. No fixed timetables: students progress at their own pace within the intake, which makes it possible to combine with work.
Each module combines theory, guided reading of the original standard and applied exercises. The working software is R, Python (scikit-learn), SAS, Emblem (WTW), in free, academic or evaluation versions. Case studies are based on real frequency and severity estimation procedures with exposure data, generalised linear models for pricing, and reserve monitoring in emerging portfolios. Assessment is continuous by module plus the final integrating project.
Build it end to end
Your final project follows the real engineering workflow, step by step, reviewed by your tutor.
Set out the actuarial problem of the vehicle at different levels of automation.
Define exposure measures based on usage data and driving mode.
Estimate frequency and severity using appropriate statistical models.
Design products, prices and reinsurance structures for the new claims profile.
Calculate and monitor reserves under Solvency II and IFRS 17.
Where this takes you
Requirements
- No prior qualification is required.
- Internet connection and a computer capable of running the programme's software.
- Sufficient level of Spanish to follow technical regulatory texts.
Ready to start?
Send your application today. Our admissions team replies within 72 hours with your study plan and funding options.
Frequently asked questions
The programme comprises 300 total hours spread over 3 to 5 months. That is between 10 and 15 hours per week on average, compatible with a full-time job.
You work with R, Python (scikit-learn), SAS, Emblem (WTW). Free, academic or evaluation versions are used, and the tutor indicates the free alternative where one exists.
A SEIUM diploma upon passing the continuous assessment and the integrating project. It is in-house training, not an official qualification from the Ministry.
Yes. Modules passed in a course or postgraduate diploma in the same area are recognised towards the advanced programme. Check the recognition policy when you enrol.
Related programmes
Insurance and Blockchain Course under Regulatory Frameworks
Online 300-hour course in insurance and blockchain under regulatory frameworks. 6 modules covering Regulation (EU) 2022/2554 (Digital Operational Resilience Act, DORA), Regulation (EU) 2016/679 (GDPR) and…
UX in Digital Insurance Course
Online 300 h course in UX in digital insurance. 6 modules covering WCAG 2.2 (web accessibility guidelines), Directive (EU) 2019/882 (accessibility requirements for products and services)…
Course in Customer Experience in Claims Processes
Online 300-hour course in customer experience in claims processes. 6 modules with ISO 23592 (customer service excellence), ISO 10002 (complaints handling) and Qualtrics. Assigned tutor and…
More in Insurance, Risk & Actuarial Data
All Insurance, Risk & Actuarial Data programmes → · How to apply · Fees & financing · Scholarships